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Space matters: host spatial structure and the dynamics of plague transmission

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  • Russell, Robin E.
  • Walsh, Daniel P.
  • Samuel, Michael D.
  • Grunnill, Martin D.
  • Rocke, Tonie E.

Abstract

The development of models to elucidate the transmission pathways and dynamics of wildlife diseases remains challenging. Sylvatic plague, caused by the bacterium Yersinia pestis (Yp), is an infectious zoonotic disease that primarily affects wild rodents, including prairie dogs (Cynomys spp.) in North America. Proposed transmission pathways for Yp include flea bites, direct contacts between hosts, and environmental reservoirs (e.g. soil, carcasses). We developed a spatially explicit, agent-based model of Yp transmission to explore the effects of alternative transmission pathways, different disease initiation mechanisms (host or fleas), parameter uncertainty, and spatial structure of hosts. A particularly novel aspect of our model was the integration of ecological models with traditional disease models. Specifically, we used estimates from spatial capture-recapture models to generate data-driven spatial distributions, densities, and contact rates to capture the spatial structure of prairie dogs. We simulated ~9 million scenarios across a wide range of parameter values and conducted sensitivity analyses to determine the most influential parameters on the number of flea-days (sum of the mean number of fleas on hosts each day of the simulation), number of newly infected hosts per day, the time to depopulation (<20 prairie dogs remaining), and the proportion of the prairie dog population remaining at the end of the simulation (after 150 days). When including spatial structure, we found the probability of transmission via environmental sources of Yp (i.e. carcasses) had the greatest influence on model results when Yp infection was initiated in prairie dog hosts, rather than in fleas. Conversely, the mechanism of transmission by fleas to prairie dogs had the greatest influence on model results when Yp infection was initiated in fleas (i.e. via introduction by carnivores, a migrant prairie dog, or other mammalian host). Uncertainty in parameter estimates, particularly those related to the transmission pathways of Yp, continue to hamper efforts to realistically model plague dynamics in wild rodents. Our results elucidate the complexity of the flea-plague-prairie dog system and reiterate the importance of research on Yp transmission mechanisms to provide a full understanding of this disease. Our results also emphasize the importance of realistic estimates of spatial structure for exploring transmission dynamics of wildlife diseases and provide a framework for generating a data-driven description of spatial structure.

Suggested Citation

  • Russell, Robin E. & Walsh, Daniel P. & Samuel, Michael D. & Grunnill, Martin D. & Rocke, Tonie E., 2021. "Space matters: host spatial structure and the dynamics of plague transmission," Ecological Modelling, Elsevier, vol. 443(C).
    • Handle: RePEc:eee:ecomod:v:443:y:2021:i:c:s0304380021000235
    DOI: 10.1016/j.ecolmodel.2021.109450
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    References listed on IDEAS

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    1. Laperrière, Vincent & Brugger, Katharina & Rubel, Franz, 2016. "Cross-scale modeling of a vector-borne disease, from the individual to the metapopulation: The seasonal dynamics of sylvatic plague in Kazakhstan," Ecological Modelling, Elsevier, vol. 342(C), pages 34-48.
    2. El Saadi, N. & Bah, A. & Mahdjoub, T. & Kribs, C., 2020. "On the sylvatic transmission of T. cruzi, the parasite causing Chagas disease: a view from an agent-based model," Ecological Modelling, Elsevier, vol. 423(C).
    3. Lambert, Sébastien & Gilot-Fromont, Emmanuelle & Toïgo, Carole & Marchand, Pascal & Petit, Elodie & Garin-Bastuji, Bruno & Gauthier, Dominique & Gaillard, Jean-Michel & Rossi, Sophie & Thébault, Anne, 2020. "An individual-based model to assess the spatial and individual heterogeneity of Brucella melitensis transmission in Alpine ibex," Ecological Modelling, Elsevier, vol. 425(C).
    4. D. L. Borchers & M. G. Efford, 2008. "Spatially Explicit Maximum Likelihood Methods for Capture–Recapture Studies," Biometrics, The International Biometric Society, vol. 64(2), pages 377-385, June.
    5. Kieran Alden & Mark Read & Jon Timmis & Paul S Andrews & Henrique Veiga-Fernandes & Mark Coles, 2013. "Spartan: A Comprehensive Tool for Understanding Uncertainty in Simulations of Biological Systems," PLOS Computational Biology, Public Library of Science, vol. 9(2), pages 1-9, February.
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    1. Hanley, Brenda J. & Carstensen, Michelle & Walsh, Daniel P. & Christensen, Sonja A. & Storm, Daniel J. & Booth, James G. & Guinness, Joseph & Them, Cara E. & Ahmed, Md Sohel & Schuler, Krysten L., 2022. "Informing Surveillance through the Characterization of Outbreak Potential of Chronic Wasting Disease in White-Tailed Deer," Ecological Modelling, Elsevier, vol. 471(C).

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